Publications
2018
Papers in international journals
- P. Bándi, O. Geessink, Q. Manson, M. van Dijk, M. Balkenhol, M. Hermsen, B. Bejnordi, B. Lee, K. Paeng, A. Zhong, Q. Li, F. Zanjani, S. Zinger, K. Fukuta, D. Komura, V. Ovtcharov, S. Cheng, S. Zeng, J. Thagaard, A. Dahl, H. Lin, H. Chen, L. Jacobsson, M. Hedlund, M. Cetin, E. Halici, H. Jackson, R. Chen, F. Both, J. Franke, H. Kusters-Vandevelde, W. Vreuls, P. Bult, B. van Ginneken, J. van der Laak and G. Litjens, "From detection of individual metastases to classification of lymph node status at the patient level: the CAMELYON17 challenge", IEEE Transactions on Medical Imaging, 2018;38(2):550-560.
- C. Reijnen, H. Kusters-Vandevelde, K. Abbink, P. Zusterzeel, A. van Herwaarden, J. van der Laak, L. Massuger, M. Snijders, J. Pijnenborg and J. Bulten, "Quantification of Leydig cells and stromal hyperplasia in the postmenopausal ovary of women with endometrial carcinoma", Human Pathology, 2018.
- S. Balocco, F. Ciompi, J. Rigla, X. Carrillo, J. Mauri and P. Radeva, "Assessment Of Intra-coronary Stent Location And Extension In Intravascular Ultrasound Sequences", Medical Physics, 2018;46(2):484-493.
- M. Silva, M. Prokop, C. Jacobs, G. Capretti, N. Sverzellati, F. Ciompi, B. van Ginneken, C. Schaefer-Prokop, C. Galeone, A. Marchiano and U. Pastorino, "Long-term Active Surveillance of Screening Detected Subsolid Nodules is a Safe Strategy to Reduce Overtreatment", Journal of Thoracic Oncology, 2018;13:1454-1463.
- D. Tellez, M. Balkenhol, I. Otte-Holler, R. van de Loo, R. Vogels, P. Bult, C. Wauters, W. Vreuls, S. Mol, N. Karssemeijer, G. Litjens, J. van der Laak and F. Ciompi, "Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks", IEEE Transactions on Medical Imaging, 2018;37(9):2126 - 2136.
- A. Baidoshvili, A. Bucur, J. van Leeuwen, J. van der Laak, P. Kluin and P. van Diest, "Evaluating the benefits of digital pathology implementation: time savings in laboratory logistics", Histopathology, 2018;73(5):784-794.
- B. Ehteshami Bejnordi, M. Mullooly, R. Pfeiffer, S. Fan, P. Vacek, D. Weaver, S. Herschorn, L. Brinton, B. van Ginneken, N. Karssemeijer, A. Beck, G. Gierach, J. van der Laak and M. Sherman, "Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies", Modern Pathology, 2018;31(10):1502-1512.
- A. Baidoshvili, N. Stathonikos, G. Freling, J. Bart, N. 't Hart, J. van der Laak, J. Doff, B. van der Vegt, M. Kluin Philip and P. van Dies, "Validation of a whole-slide image-based teleconsultation network", Histopathology, 2018;73:777-783.
- G. Litjens, P. Bándi, B. Ehteshami Bejnordi, O. Geessink, M. Balkenhol, P. Bult, A. Halilovic, M. Hermsen, R. van de Loo, R. Vogels, Q. Manson, N. Stathonikos, A. Baidoshvili, P. van Diest, C. Wauters, M. van Dijk and J. van der Laak, "1399 H&E-stained sentinel lymph node sections of breast cancer patients: the CAMELYON dataset", GigaScience, 2018;7(6):1-8.
- B. Bejnordi, G. Litjens and J. van der Laak, "Machine Learning Compared With Pathologist Assessment-Reply", Journal of the American Medical Association, 2018;319(16):1726.
- M. Silva, C. Schaefer-Prokop, C. Jacobs, G. Capretti, F. Ciompi, B. van Ginneken, U. Pastorino and N. Sverzellati, "Detection of Subsolid Nodules in Lung Cancer Screening: Complementary Sensitivity of Visual Reading and Computer-Aided Diagnosis", Investigative Radiology, 2018;53(8):441-449.
- K. Chung, F. Ciompi, J. Scholten E. Th. Goo, M. Prokop, C. Jacobs, B. van Ginneken and C. Schaefer-Prokop, "Visual Discrimination of Screen-detected Persistent from Transient Subsolid Nodules: an Observer Study", PLoS One, 2018;13(2):e0191874.
- J. Charbonnier, K. Chung, E. Scholten, E. van Rikxoort, C. Jacobs, N. Sverzellati, M. Silva, U. Pastorino, B. van Ginneken and F. Ciompi, "Automatic segmentation of the solid core and enclosed vessels in subsolid pulmonary nodules", Scientific Reports, 2018;8(1):646.
Preprints
- G. Mooij, I. Bagulho and H. Huisman, "Automatic segmentation of prostate zones", arXiv:1806.07146, 2018.
- Z. Li, Z. Hu, J. Xu, T. Tan, H. Chen, Z. Duan, P. Liu, J. Tang, G. Cai, Q. Ouyang, Y. Tang, G. Litjens and Q. Li, "Computer-aided diagnosis of lung carcinoma using deep learning - a pilot study", arXiv:1803.05471, 2018.
Papers in conference proceedings
- W. Bulten and G. Litjens, "Unsupervised Prostate Cancer Detection on H&E using Convolutional Adversarial Autoencoders", Medical Imaging with Deep Learning, 2018.
- D. Geijs, M. Intezar, J. van der Laak and G. Litjens, "Automatic color unmixing of IHC stained whole slide images", Medical Imaging, 2018;10581.
- F. Zanjani, S. Zinger, B. Bejnordi, J. van der Laak and P. de With, "Stain normalization of histopathology images using generative adversarial networks", 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), 2018.
- Z. Swiderska-Chadaj, H. Pinckaers, M. van Rijthoven, M. Balkenhol, M. Melnikova, O. Geessink, Q. Manson, G. Litjens, J. van der Laak and F. Ciompi, "Convolutional Neural Networks for Lymphocyte detection in Immunohistochemically Stained Whole-Slide Images", Medical Imaging with Deep Learning, 2018.
- D. Tellez, J. van der Laak and F. Ciompi, "Gigapixel Whole-Slide Image Classification Using Unsupervised Image Compression And Contrastive Training", Medical Imaging with Deep Learning, 2018.
- D. Tellez, M. Balkenhol, N. Karssemeijer, G. Litjens, J. van der Laak and F. Ciompi, "H&E stain augmentation improves generalization of convolutional networks for histopathological mitosis detection", Medical Imaging, 2018;10581.
- M. van Rijthoven, Z. Swiderska-Chadaj, K. Seeliger, J. van der Laak and F. Ciompi, "You Only Look on Lymphocytes Once", Medical Imaging with Deep Learning, 2018.
- J. Bokhorst, L. Rijstenberg, D. Goudkade, I. Nagtegaal, J. van der Laak and F. Ciompi, "Automatic Detection of Tumor Budding in Colorectal Carcinoma with Deep Learning", Computational Pathology and Ophthalmic Medical Image Analysis, 2018.
- W. Bulten, C. de Kaa, J. van der Laak and G. Litjens, "Automated segmentation of epithelial tissue in prostatectomy slides using deep learning", Medical Imaging, 2018;10581:105810S.
- T. de Bel, M. Hermsen, J. van der Laak, G. Litjens, B. Smeets and L. Hilbrands, "Automatic segmentation of histopathological slides of renal tissue using deep learning", Medical Imaging 2018: Digital Pathology, 2018.
Abstracts
- F. Zanjani, S. Zinger, B. Bejnordi, J. van der Laak and P. de With, "Histopathology stain-color normalization using deep generative models", Medical Imaging with Deep Learning, 2018.
- E. Smeets, J. Teuwen, J. van der Laak, M. Gotthardt, F. Ciompi and E. Aarntzen, "Tumor heterogeneity as a PET-biomarker predicts overall survival of pancreatic cancer patients", European Society for Molecular Imaging, 2018.
- M. Hermsen, T. de Bel, M. den Boer, E. Steenbergen, J. Kers, S. Florquin, B. Smeets, L. Hilbrands and J. van der Laak, "Glomerular detection, segmentation and counting in PAS-stained histopathological slides using deep learning", Dutch Federation of Nephrology (NfN) Fall Symposium, 2018.
- H. Pinckaers and G. Litjens, "Training convolutional neural networks with megapixel images", Medical Imaging with Deep Learning, 2018.
Master theses
- M. den Boer, "Automated structure segmentation and lymphocyte detection in kidney transplant whole slide images using a convolutional neural network", Master thesis, 2018.
Other publications
- T. de Bel, M. Hermsen, G. Litjens and J. van der Laak, "Structure Instance Segmentation in Renal Tissue: A Case Study on Tubular Immune Cell Detection", Computational Pathology and Ophthalmic Medical Image Analysis, 2018:112-119.